Andrew Golightly

23 papers A* 1A 1Journal 19Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Bayesian classification of OXPHOS deficient skeletal myofibres.
PLoS Comput. Biol.
Jordan Childs, Tiago Bernardino Gomes, Amy E. Vincent, Andrew Golightly, Conor Lawless
2024 J jnl
Bayesian inference for a spatio-temporal model of road traffic collision data.
J. Comput. Sci.
Nicola Hewett, Andrew Golightly, Lee Fawcett, Neil Thorpe
2023 J jnl
A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant.
Comput. Stat. Data Anal.
Naomi E. Hannaford, Sarah E. Heaps, Tom M. W. Nye, Thomas P. Curtis, Ben Allen, Andrew Golightly, Darren J. Wilkinson
2023 J jnl
Accelerating Bayesian inference for stochastic epidemic models using incidence data.
Stat. Comput.
Andrew Golightly, Laura E. Wadkin, Sam A. Whitaker, Andrew W. Baggaley, Nick G. Parker, Theodore Kypraios
2023 J jnl
Accelerating inference for stochastic kinetic models.
Comput. Stat. Data Anal.
Tom E. Lowe, Andrew Golightly, Chris Sherlock
2023 J jnl
Exact Bayesian Inference for Discretely Observed Markov Jump Processes Using Finite Rate Matrices.
J. Comput. Graph. Stat.
Chris Sherlock, Andrew Golightly
2022 J jnl
Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes.
Stat. Comput.
Andrew Golightly, Chris Sherlock
2021 J jnl
Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms.
Comput. Stat. Data Anal.
Samuel Wiqvist, Andrew Golightly, Ashleigh T. McLean, Umberto Picchini
2021 A conf
The neural moving average model for scalable variational inference of state space models.
UAI
Thomas Ryder, Dennis Prangle, Andrew Golightly, Isaac Matthews
2020 J jnl
Sequential Bayesian inference for spatio-temporal models of temperature and humidity data.
J. Comput. Sci.
Yingying Lai, Andrew Golightly, Richard J. Boys
2019 J jnl
Correlated pseudo-marginal schemes for time-discretised stochastic kinetic models.
Comput. Stat. Data Anal.
Andrew Golightly, Emma Bradley, Tom E. Lowe, Colin S. Gillespie
2019 J jnl
Efficient sampling of conditioned Markov jump processes.
Stat. Comput.
Andrew Golightly, Chris Sherlock
2019 J jnl
Scalable approximate inference for state space models with normalising flows.
CoRR
Tom Ryder, Andrew Golightly, Isaac Matthews, Dennis Prangle
2018 J jnl
Black-Box Autoregressive Density Estimation for State-Space Models.
CoRR
Tom Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle
2018 A* conf
Black-Box Variational Inference for Stochastic Differential Equations.
ICML
Thomas Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle
2018 J jnl
Efficient SMC
Stat. Comput.
Andrew Golightly, Theodore Kypraios
2017 J jnl
Improved bridge constructs for stochastic differential equations.
Stat. Comput.
Gavin A. Whitaker, Andrew Golightly, Richard J. Boys, Chris Sherlock
2015 J jnl
Delayed acceptance particle MCMC for exact inference in stochastic kinetic models.
Stat. Comput.
Andrew Golightly, Daniel A. Henderson, Chris Sherlock
2010 — ch.
Markov Chain Monte Carlo Algorithms for SDE Parameter Estimation.
Learning and Inference in Computational Systems Biology
Darren J. Wilkinson, Andrew Golightly
2008 J jnl
Bayesian inference for nonlinear multivariate diffusion models observed with error.
Comput. Stat. Data Anal.
Andrew Golightly, Darren J. Wilkinson
2006 J jnl
Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models.
J. Comput. Biol.
Andrew Golightly, Darren J. Wilkinson
2006 J jnl
Bayesian sequential inference for nonlinear multivariate diffusions.
Stat. Comput.
Andrew Golightly, Darren J. Wilkinson
2002 — conf
An experimental speech to graphics system.
CHINZ
Andrew Golightly, Tony Smith